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The Tibet AS γ experiment has been observing cosmic gamma rays and cosmic rays in the energy range from teraelectron volts to several tens of petaelectron volts with a surface detector array since 1990. The derivation of cosmic gamma-ray flux is made by finding the excess distribution of the arrival direction of air showers above background cosmic rays. In 2014, the underground water Cherenkov muon detector (MD) was added to separate cosmic gamma rays from the background on the basis of the muon-less feature of the air showers of gamma-ray origin; hybrid observations using these two detectors were started at this time. In the present study, we developed methods to separate gamma-ray-induced air showers and hadronic cosmic-ray-induced ones using the measured particle number density distribution to improve the sensitivity of cosmic gamma-ray measurements using the Tibet air shower array data alone before the installation of the MD. We tested two approaches based on neural networks. The first method used feature values representing the lateral spread of the secondary particles, and the second method used the shower image data. To compare the separation performance of each method, we analyzed Monte Carlo air shower events in the vertically incident direction with mono-initial-energy gamma rays and protons. When discriminated by a single feature, the feature with the highest separation performance has an area under the curve (AUC) value of 0.701 for a gamma-ray energy of 10 TeV and 0.808 for 100 TeV. A separation method with a multilayer perceptron (MLP) based on multiple features has AUC values of 0.761 for a gamma-ray energy of 10 TeV and 0.854 for 100 TeV, which represents an improvement of approximately 5% in the AUC value compared with the single-feature case. We also found that the feature values that effectively contribute to the separation vary depending on the energy. A separation method with a convolutional neural network (CNN) using the shower image data has AUC values of 0.781 for a gamma-ray energy of 10 TeV and 0.901 for 100 TeV, which are approximately 5% higher than those of the MLP method. We applied the CNN separation method to Monte Carlo gamma-ray and cosmic-ray events from the Crab Nebula in the energy range 10–100 TeV. The AUC values range from 0.753 to 0.879, and the significance of the observed gamma-ray excess is improved by 1.3 to 1.8 times compared with the case without the separation procedure.

In the Large High Altitude Air Shower Observatory (LHAASO), one square kilometer array (KM2A), with 5242 electromagnetic particle detectors (EDs) and 1171 muon detectors (MDs), is designed to study ultra-high energy gamma-ray astronomy and cosmic ray physics. The remoteness and numerous detectors extremely demand a robust and automatic calibration procedure. In this paper, a self-calibration method which relies on the measurement of charged particles within the extensive air showers is proposed. The method is fully validated by Monte Carlo simulation and successfully applied in a KM2A prototype array experiment. Experimental results show that the self-calibration method can be used to determine the detector time offset constants at the sub-nanosecond level and the number density of particles collected by each ED with an accuracy of a few percents, which are adequate to meet the physical requirements of LHAASO experiment. This software calibration also offers an ideal method to realtime monitor the detector performances for next generation ground-based EAS experiments covering an area above square kilometers scale. [ABSTRACT FROM AUTHOR]

Previous measurements of the composition of Ultra-High Energy Cosmic Rays (UHECRs) made by the High Resolution Fly’s Eye (HiRes) and Pierre Auger Observatory (PAO) are seemingly contradictory, but utilize different detection methods, as HiRes was a stereo detector and PAO is a hybrid detector. The five year Telescope Array (TA) Middle Drum hybrid composition measurement is similar in some, but not all, respects in methodology to PAO, and good agreement is evident between data and a light, largely protonic, composition when comparing the measurements to predictions obtained with the QGSJetII-03 and QGSJet-01c models. These models are also in agreement with previous HiRes stereo measurements, confirming the equivalence of the stereo and hybrid methods. The data is incompatible with a pure iron composition, for all models examined, over the available range of energies. The elongation rate and mean values of X max are in good agreement with Pierre Auger Observatory data. This analysis is presented using two methods: data cuts using simple geometrical variables and a new pattern recognition technique. [ABSTRACT FROM AUTHOR]

Abstract: The Telescope Array (TA) experiment, located in the western desert of Utah, USA, is designed for the observation of extensive air showers from extremely high energy cosmic rays. The experiment has a surface detector array surrounded by three fluorescence detectors to enable simultaneous detection of shower particles at ground level and fluorescence photons along the shower track. The TA surface detectors and fluorescence detectors started full hybrid observation in March, 2008. In this article we describe the design and technical features of the TA surface detector. [Copyright &y& Elsevier]

Telescope Array (TA) is the largest ultrahigh energy cosmic-ray (UHECR) observatory in the Northern Hemisphere. It explores the origin of UHECRs by measuring their energy spectrum, arrival-direction distribution, and mass composition using a surface detector (SD) array covering approximately 700 km 2 and fluorescence detector (FD) stations. TA has found evidence for a cluster of cosmic rays with energies greater than 57 EeV. In order to confirm this evidence with more data, it is necessary to increase the data collection rate. We have begun building an expansion of TA that we call TAx4. In this paper, we explain the motivation, design, technical features, and expected performance of the TAx4 SD. We also present TAx4's current status and examples of the data that have already been collected. [ABSTRACT FROM AUTHOR]